Monitoring COVID-19 and Influenza: The Added Value of a Severe Acute Respiratory Infection Surveillance System in Portugal

Background Severe acute respiratory infections (SARI) surveillance is recommended to assess the severity of respiratory infections disease. In 2021, the National Institute of Health Doutor Ricardo Jorge, in collaboration with two general hospitals, implemented a SARI sentinel surveillance system based on electronic health registries. We describe its application in the 2021/2022 season and compare the evolution of SARI cases with the COVID-19 and influenza activity in two regions of Portugal. Methods The main outcome of interest was the weekly incidence of patients hospitalized due to SARI, reported within the surveillance system. SARI cases were defined as patients containing ICD-10 codes for influenza-like illness, cardiovascular diagnosis, respiratory diagnosis, and respiratory infection in their primary admission diagnosis. Independent variables included weekly COVID-19 and influenza incidence in the North and Lisbon and Tagus Valley regions. Pearson and cross-correlations between SARI cases, COVID-19 incidence and influenza incidence were estimated. Results A high correlation between SARI cases or hospitalizations due to respiratory infection and COVID-19 incidence was obtained (ρ = 0.78 and ρ = 0.82, respectively). SARI cases detected the COVID-19 epidemic peak a week earlier. A weak correlation was observed between SARI and influenza cases (ρ = −0.20). However, if restricted to hospitalizations due to cardiovascular diagnosis, a moderate correlation was observed (ρ = 0.37). Moreover, hospitalizations due to cardiovascular diagnosis detected the increase of influenza epidemic activity a week earlier. Conclusion In the 2021/2022 season, the Portuguese SARI sentinel surveillance system pilot was able to early detect the COVID-19 epidemic peak and the increase of influenza activity. Although cardiovascular manifestations associated with influenza infection are known, more seasons of surveillance are needed, to confirm the potential use of cardiovascular hospitalizations as an indicator of influenza activity.


Background
In response to SARS-CoV-2 emergence, substantial changes occurred in respiratory infection surveillance activities at inpatient and outpatient levels, moving the focus from disease specifc surveillance of infuenza and other respiratory viruses into SARS-CoV-2 [1]. With unprecedented nonpharmacological measures in place to control the COVID-19 pandemic, a decrease in other respiratory virus incidence was observed worldwide, with low or almost inexistent circulation of infuenza during 2020/ 2021 compared with previous seasons. However, in the 2021/

Setting and Study Design.
Tis is a retrospective surveillance study implemented in two Portuguese university general hospitals, Centro Hospitalar Universitário de São João and Centro Hospitalar Universitário Lisboa Central, located in the main cities (Oporto and Lisbon, respectively) of the two most populated regional health administrations (North and Lisbon and Tagus Valley regions, respectively) of the country. Tese sentinel sites were selected among the I-MOVE (Infuenza-Monitoring Vaccine Efectiveness in Europe) hospital network and the Portuguese Laboratory Network for the Diagnosis of Infuenza Infection [20][21][22][23]. Detailed information on the participating hospitals and respective wards is provided in Table 1.

SARI Case
Identifcation. SARI cases were identifed among those who have been admitted for at least 24h, in one of the participating hospitals. In the emergency room (ER) a diagnosis at admission, coded according to the ICD-10, is registered by the ER team for every patient [13]. Anonymised case-based data regarding inpatients admitted to all wards were made available on a weekly basis by the sentinel hospitals and included patients' sex, age, date of admission, and primary admission diagnosis. All reporting procedures for each hospital are automated, routinely programmed, and in accordance with legal and ethical requirements. SARI cases were defned as patients containing any ICD-10 codes for infuenza-like illness, cardiovascular diagnosis, respiratory diagnosis, and respiratory infection in their primary admission diagnosis. Tese ICD-10 codes were selected after a literature research and based on the Integrated Monitoring of Vaccines in Europe project (I-MOVE+) (see Table 2 for ICD-10 codes) [9,[14][15][16][17][18][19]. We categorized the most common signs and symptoms related to infuenza infection into the infuenza-like illness group, while acute cardiovascular events commonly associated with respiratory infections were categorized into cardiovascular diagnosis, and the most common respiratory infections were categorized into the respiratory infections group. All remaining respiratory signs and symptoms and exacerbation of chronic respiratory disease (e.g., asthma) were categorized into the respiratory diagnosis group. Te generic surveillance system fow is presented in Figure 1.
Te SARI sentinel surveillance system protocol was approved by the Ethical Committees of the National Institute of Health Doutor Ricardo Jorge, Centro Hospitalar Universitário de São João, and Centro Hospitalar Universitário Lisboa Central. Given that data used within this study were pseudoanonymised and collected in the scope of epidemiological surveillance of respiratory viruses with epidemic or pandemic potential, such as infuenza and SARS-CoV-2, the need for the participants' informed consent was waived by the Ethical Committees [24]. Patient data were pseudoanonymised by the information technology personnel at each sentinel site, by removing identifable features: name, date of birth, address, and telephone numbers. Te 9-digit Portuguese National Health Service IDs were replaced with a unique and anonymous code. Te key to map Portuguese National Health Service IDs to anonymous IDs was secured at each sentinel site.

Population under Surveillance.
Te population under surveillance consists in all individuals living in the catchment area of each sentinel site, who would usually seek healthcare at the site when they get sick. We reviewed the hospital discharge registry database (BIMH-Identity Card for Hospital Morbidity) that covers all admission in public hospitals in Portugal mainland, in order to prepare a hot spot map based on SARI cases according to the place of residency. Tis map corresponded to at least 80% of SARI cases hospitalized at each sentinel site in the last three years [25]. For each selected municipality within the spot map, we computed the proportion of SARI admitted by participating hospital among all SARI admissions registered in the municipality. Finally, to estimate individual contribution of each selected municipality to population under surveillance, we applied previously estimated proportions to most recent resident population fgures for municipalities [26]. Please see Table 3 for detailed information on the population under surveillance for each sentinel site.

Statistical Analyses.
Descriptive statistics (count and percentages) were used to characterize distribution of SARI cases reported by surveillance system. A time-series analysis was performed using the weekly number of SARI cases and two indicators: (1) the weekly number of samples positive for SARS-CoV-2 and (2) the weekly number of samples positive for infuenza. Pearson correlation (0 ≤ ρ < 0.3-weak correlation; 0.3 ≤ ρ < 0.7-moderate correlation; and 0.7 ≤ ρ-strong correlation) and cross-correlations between SARI cases and each indicator were estimated [28]. Te cross-correlation study allows the identifcation of the lag (delay) between two time-series. If a higher crosscorrelation value is found on lag 0, the values of the frst series (SARI cases) are correlated with the values of the second series (COVID-19 cases or infuenza positive samples) without delay. If the higher cross-correlation value is found to have a negative lag, the values of the frst series are correlated with the values of the second series with a delay of lag weeks, and if the higher crosscorrelation value is found to have a positive lag, the values of the frst series are correlated with the values of the second series, and the second series precedes the frst in lag weeks [29].  Figure 1: Severe acute respiratory infections surveillance system fowchart. Te patient circuit is identifed using solid arrows; electronic information fow is identifed using dashed arrows. SARI: severe acute respiratory infection.

Results
From a total of 32,011 hospital admissions that were notifed by the participating hospitals, between week 40 2021 and week 20 2022, 3,563 encompassed SARI-related diagnoses corresponding to 11.1% of all hospital admissions and to a cumulative SARI incidence rate of 394.1 per 100,000 population. However, the proportion of SARI cases varied during the study period, ranging from 7.4% on week 41 2021 to 16.8% on week 03 2022 (see Figure2).
Te general characteristics of the SARI cases are summarised in Table 4. Te age group (4.5% ≤ 0-4 years; 2.5% 5-14 years; 5.2% 15-44 years; 15.9% 45-64 years; 28.4% 65-79 years; and 43.7% ≥ 80 years) and diagnosis distributions (12.8% infuenza-like illness; 27.7% cardiovascular diagnosis; 6.4% respiratory diagnosis; and 58.4% respiratory infection) remained similar over the full observation period, but a relative increase in SARI in the age group over 80 years old was registered in weeks coincident with a high number of hospitalizations due to respiratory infections or cardiovascular diagnosis (Figure 3). Additionally, the pattern in admissions due to infections appears to follow the pattern of COVID-19 cases, whereas the increase in cardiovascular diagnosis (in weeks 10 and 11, 2022) appears to be time coincident with an increase in infuenza cases (Figure 3).
Graphical patterns between SARI, COVID-19, and infuenza cases was confrmed by cross-correlation analysis ( Table 5). A high correlation between SARI cases or hospitalizations due to respiratory infection and COVID-19 incidence was obtained (ρ � 0.78 and ρ � 0.82, respectively). Moreover, weekly SARI cases detected COVID-19 epidemic peak for about a week earlier (highest cross-correlation value for lag � −1). A weak correlation was observed between SARI and infuenza cases (ρ � −0.20). However, if restricted to hospitalizations due to cardiovascular diagnosis, a moderate correlation was observed (ρ � 0.37). Moreover, hospitalizations due to cardiovascular diagnosis detected the increase of infuenza epidemic activity for about a week earlier (highest cross-correlation value for lag � −1). Tis early warning was not observed between hospitalizations due to cardiovascular diagnosis and COVID-19 cases.

Discussion
Our analyses demonstrated the potential of a register-based SARI hospital sentinel surveillance system.   Canadian Journal of Infectious Diseases and Medical Microbiology hospitalizations due to viral pneumonia had already proven to be an asset regarding the early detection of COVID-19 outbreaks in Portugal during the early stages of the pandemic, which is in line with results from this work [12]. We note that the modest increase observed in SARI cases comparing to the steep increase in COVID-19 cases, from week 50 2021 onwards, is consistent with the increased transmissibility and decreased pathogenicity of the Omicron variant [32]. In late December, Omicron swiftly replaced the then-dominant Delta variant in Portugal, resulting in a skyrocketing number of COVID-19 cases [33]. However, this increase did not result in a proportional hospital burden because, although Omicron has a 3.31-fold higher transmissibility than Delta, patients with Omicron infection are signifcantly less likely to be admitted to hospitals, require oxygen, or being admitted to ICUs [34,35].
Hospitalizations due to cardiovascular diagnosis were able to early detect infuenza activity in the North and Tagus Valley regions, suggesting this indicator might be used to monitor infuenza activity. However, this early warning was not observed between hospitalizations due to cardiovascular diagnosis and COVID-19 cases. A review of the literature, also found peak infuenza season to be associated with increased cardiovascular hospitalizations, contrasting with a decrease of approximately 50% in cardiovascular hospitalizations during the COVID-19 pandemic [36]. One possible explanation might be related to deferred care during times of high COVID-19 incidence, as several studies showed a signifcant decline in the number of patients seeking emergency care for cardiac events during the pandemic, citing hesitancy or fear as the main cause [37,38]. In addition, the lack of exposure of the population to the infuenza virus during the COVID-19 pandemic and the vaccination mismatch, might have resulted in increased severe forms of disease when infected with infuenza, including cardiovascular complications during the 2021/2022 season [39][40][41]. Terefore, while the association between infuenza and cardiovascular manifestations is known, more seasons of SARI surveillance are needed, to confrm the strength of the association between hospitalizations due to cardiovascular diagnosis and infuenza activity [42].
Even though, the representativeness of data is a concern as paediatrics wards are only included in one of the sentinel sites, the distribution of SARI cases stratifed by age, and the relative increase in the age group above 80 years old in periods with a high incidence of COVID-19 and infuenza, was expected as older individuals have an increased risk of hospitalization during epidemic periods of respiratory infections [43,44].
Te fndings of this study should be interpreted by taking the following limitations into account. First, the selected data are from two sentinel hospitals from 2 out of 5 health administration regions in the country, meaning that they are not representative of severe acute hospitalizations in Portugal. Second, using only primary diagnoses could capture mainly the population without major comorbidities, in particular, in hospitalizations due to infuenza-like illness. SARI cases with underlying chronic disease (e.g., cardiovascular diseases) may have their comorbidity coded in the primary diagnosis and ICD-10 codes corresponding to symptoms of infuenza-like illness in their secondary diagnosis, as the exacerbation of the  Canadian Journal of Infectious Diseases and Medical Microbiology chronic disease could play a major role in their hospitalization [42]. Tis is in line with the increase in hospitalizations due to cardiovascular diagnosis during the epidemic activity of Infuenza in Portugal (between March and May 2022). Finally, the syndromic SARI case defnition is based on the clinical documentation for the hospitalization at admission, which is not designed for surveillance. Its heavy reliance on clinical presentation, especially, when laboratory diagnosis is frequently not yet available, can create potential uncertainty in data interpretation. Shortness of breath, for example, may be a symptom resulting either from cardiovascular disease or from an infection by a respiratory pathogen [45]. Te SARI surveillance system described in this study has several strengths that are worth highlighting. Te sentinel sites included in this surveillance are general hospitals and, therefore, are more likely to be representative of the general population than specialty or tertiary care referral hospitals. Te option for a SARI proxy case defnition identifed using ICD-10 codes, instead of applying WHO's clinical case defnition (hospitalized patient with fever, cough, and onset of disease within the last 10 days), which would be collected through a questionnairebased surveillance, was made to minimize the burden of the healthcare professionals [6]. We note that physicians who participated in a study conducted in Portugal with the aim to measure seasonal infuenza vaccine efectiveness (EVA hospital study) and primary care clinicians from Portuguese sentinel sites perceived data collection as time-consuming, especially during infuenza and COVID-19 epidemic peaks [20,46]. On the other hand, it is important to note that all reporting procedures for each hospital are automated and routinely programmed, therefore, minimizing workload and guaranteeing timeliness. Additionally, the selected sentinel sites have prior experience in surveillance and at least one hospital has a human resource entirely dedicated to this task, thus, ensuring data quality and commitment to the surveillance system. Finally, the methodology we used to estimate the catchment population can be replicated in other potential sentinel surveillance sites. It is also reassuring that the BIMH database used for these estimates accounts for more than 70% of all national hospital admissions. Finally, stressing the importance of sustainability of this surveillance system, estimating the catchment population did not result in extra work for the hospitals.
Linkage of laboratory with clinical data is being tested as, in the long term, our goal is to establish an integrated and automated SARI syndromic surveillance system combined with laboratory outcomes, in sentinel hospitals evenly geographically distributed across Portugal. Tis step will aid in understanding the relative contribution of respiratory viruses among SARI cases, especially, when multiple respiratory viruses are cocirculating. Following WHO and ECDC guidelines for respiratory virus surveillance, all specimens taken from SARI sentinel surveillance will be tested at the sentinel sites, using multiplex polymerase chain reaction (PCR) assays to simultaneously detect infuenza viruses, SARS-CoV-2, and other respiratory viruses that have a major impact on healthcare systems [6]. Additionally, all sentinel specimens positive for infuenza viruses or SARS-CoV-2 will be shared for sequencing at the Portuguese Reference Laboratory for Infuenza and other Respiratory Virus, for the purpose of monitoring SARS-CoV-2 variant and infuenza strain/lineage circulation [6]. To achieve this goal, it is also necessary to make a continuous efort in order to demonstrate the added value of epidemiological surveillance data to stakeholders within hospital sites. Tis could be achieved by integrating SARI surveillance in existing hospital programs, such as for monitoring antibiotic or antiviral use and resistance, in order to make surveillance data valuable for public health as well as patient care [47,48]. Te groups of diagnosis used to categorize SARI patients in this study were based on signs and symptoms of respiratory infection (reported in Table 1). Given that within each set, signs or symptoms of respiratory illness may difer in their sensitivity and specifcity to detect variations in infuenza and COVID-19 infection trends, we plan to study specifc diagnosis separately for each disease, and then expand or restrict ICD-10 admission codes in each group when needed. Regarding future steps in data validation analysis, the national register of hospital discharge diagnoses with specifc ICD-10 codes related to respiratory infections is available with a considerable time lag, which precludes its use for nearly realtime SARI surveillance. Discharge diagnoses are manually attributed by trained medical professionals and, therefore, using this information for retrospective analysis may help to confrm and validate results from the surveillance system based on hospital diagnosis at admission.

Conclusion
In the 2021/2022 season, the Portuguese SARI sentinel surveillance system pilot was able to early detect the COVID-19 epidemic peak, in January 2022, and the increase of infuenza activity, in March 2022. Although cardiovascular manifestations associated with infuenza infection are known, more seasons of SARI surveillance are needed, to confrm the potential use of cardiovascular hospitalizations as an indicator of infuenza activity. Combining syndromic surveillance with virological inpatient surveillance will aid in understanding the relationship between respiratory virus epidemics and disease severity.

Data Availability
Te data used to support the fndings of this study have not been made available becausethe current ethical approval does not permit their deposition.

Ethical Approval
Te SARI surveillance system protocol received approval from the Ethical Committees of the National Institute of Health Doutor Ricardo Jorge, Centro Hospitalar Universitário de São João, and Centro Hospitalar Universitário Lisboa Central. Given that data were pseudoanonymised and collected in the scope of epidemiological surveillance, the need for the participants' informed consent was waived by the Ethical Committees [49].